In Table REF  we summarize the real-world datasets used in this work.
SWaT[1]} and WADI [2]} are datasets of sensors measuring water-treatment plants.
In the test split there are annotated anoalies where the creators tampered with the water treatment systems.
Therefore, SWaT and WADI were originally proposed as anomaly detection datasets (and e.g., used in the GDN paper);
however, since the respective training sets are free of anomalies, we use them for our forecasting experiments.
